Probabilistic analysis of vulnerability to stenospermocarpy due to hygrothermal stress in 'Palmer' mangoes using a copula-based approach

Abstract

Abstract The objective of this work was to probabilistically identify susceptible seasons to the highest incidence of stenospermocarpic fruit in 'Palmer' mangoes, using univariate and copula procedures. Additionally, the impact of climatic variables on price fluctuations in the mango market was evaluated in the region of the Vale do Submédio São Francisco, Brazil. The normal, log-normal, gamma, and generalized extreme value distributions, as well as the Frank copula, were fitted to temperature and relative humidity data (2007-2018) obtained from the meteorological station of Universidade do Estado da Bahia. The adequacy of the distributions was verified using the Kolmogorov-Smirnov, Cramér-von Mises, and Anderson-Darling tests. The Frank copula is suitable for the joint modeling of the maximum temperature and minimum relative humidity. The occurrence of high temperatures and low relative humidity affects the price of mangoes. November shows a high probability of the simultaneous occurrences of high temperatures and low relative air humidity, which makes 'Palmer' mango orchards in full bloom (or early fruiting) significantly subject to extreme weather conditions that favor higher rates of stenospermocarpy in the harvests from April to May.

Keywords

• Mangifera indica
• mango market
• weather influence